json.lua
femtolisp
json.lua | femtolisp | |
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14 | 10 | |
1,723 | 1,550 | |
- | - | |
0.0 | 0.0 | |
5 months ago | about 4 years ago | |
Lua | Scheme | |
MIT License | BSD 3-clause "New" or "Revised" License |
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json.lua
- fe: A tiny, embeddable language implemented in ANSI C
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Free mods list
One option might be to look at the Path of Building “Data” folder. If you need them in another format (e.g. json), it wouldn’t be that hard to write a Lua script to export them in your preferred format (using this json library, for example.
- Closing your program
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A question about save/load.
If you don't want to reinvent the wheels, you might want a json encoder to transform data into strings and back. Or bitser if you want better performance and smaller files in exchange for human-readability.
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Plain Text. With Lines
Honestly, I just went with JSON because there's a nice Lua library for it (thank you https://github.com/rxi/json.lua).
I haven't thought about the file format much so far, just the experience of writing in it as if it's the "ground truth". We all seldom open our text files in a hex editor.
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Open a Lua file and create Object/Array/Table
JSON https://github.com/rxi/json.lua
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Lua, Open lua file and display as a table
Get json.lua from here. Put it in your project directory alongside file1.lua.
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Cant get highscore to save
Good point. How about this? It allows you to encode/decode Lua values into/from JSON.
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Indexing / substrings
I like this json library and tend to use it for save files (also makes them easy to edit by hand while debugging). It gets angry if you use tables with a mix of string and numerical keys, but I'd advise against that anyway. I've also used binser, which is also effective and easy to use.
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Preserve previously used tag between restarts
lua json module can be found from here: https://github.com/rxi/json.lua
femtolisp
- Petalisp: Elegant High Performance Computing
- fe: A tiny, embeddable language implemented in ANSI C
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From Common Lisp to Julia
> In short, Julia is very similar to Common Lisp, but brings a lot of extra niceties to the table
This probably because Jeff Bezanson, the creator of Julia, created a Lisp prior to Julia, which I think still exists inside Julia in some fashion
https://github.com/JeffBezanson/femtolisp
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Modern Python Performance Considerations
Well let's flip this around: do you think you could write a performant minimal Python in a weekend? Scheme is a very simple and elegant idea. Its power derives from the fact that smart people went to considerable pains to distill computation to limited set of things. "Complete" (i.e. rXrs) schemes build quite a lot of themselves... in scheme, from a pretty tiny core. I suspect Jeff Bezanson spent more than a weekend writing femtolisp, but that isn't really important. He's one guy who wrote a pretty darned performant lisp that does useful computation as a passion project. Check out his readme; it's fascinating: https://github.com/JeffBezanson/femtolisp
You simply can't say these things about Python (and I generally like Python!). It's truer for PyPy, but PyPy is pretty big and complex itself. Take a look at the source for the scheme or scheme-derived language of your choice sometime. I can't claim to be an expert in any of what's going on in there, but I think you'll be surprised how far down those parens go.
The claim I was responding to asserted that lisps and smalltalks can only be fast because of complex JIT compiling. That is trueish in practice for Smalltalk and certainly modern Javascript... but it simply isn't true for every lisp. Certainly JIT-ed lisps can be extremely fast, but it's not the only path to a performant lisp. In these benchmarks you'll see a diversity of approaches even among the top performers: https://ecraven.github.io/r7rs-benchmarks/
Given how many performant implementations of Scheme there are, I just don't think you can claim it's because of complex implementations by well-resourced groups. To me, I think the logical conclusion is that Scheme (and other lisps for the most part) are intrinsically pretty optimizable compared to Python. If we look at Common Lisp, there are also multiple performant implementations, some approximately competitive with Java which has had enormous resources poured into making it performant.
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CppCast: Julia
While it uses an Algol inspired syntax, it has the same approach to OOP programing as CLOS(Common Lisp Object System), with multi-methods and protocols, it has a quite powerfull macro system like Lisp, similar REPL experience, and underneath it is powerered by femtolisp.
- Julia and the Incarceration of Lisp
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What is the smallest x86 lisp?
For a real answer, other replies have already mentioned KiloLisp, but there's also femtolisp. Also, not exactly what you're asking for, but Maru is a very compact and elegant self-hosting lisp (compiles to x86).
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lisp but small and low level?Does it make sense?
Take a look at femtolisp It has some low level features and is quite small. There is also a maintenance fork at lambdaconservatory
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Lispsyntax.jl: A Clojure-like Lisp syntax for julia
A fun Julia easter egg I recently discovered.
Running 'julia --lisp' launches a femtolisp (https://github.com/JeffBezanson/femtolisp) interpreter.
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Wisp: A light Lisp written in C++
Reminds me of the femtolisp README :)
Almost everybody has their own lisp implementation. Some programmers' dogs and cats probably have their own lisp implementations as well. This is great, but too often I see people omit some of the obscure but critical features that make lisp uniquely wonderful. These include read macros like #. and backreferences, gensyms, and properly escaped symbol names. If you're going to waste everybody's time with yet another lisp, at least do it right damnit.
https://github.com/JeffBezanson/femtolisp
What are some alternatives?
haproxy-lua-http - Simple Lua HTTP helper && client for use with HAProxy.
small-lisp - A very small lisp interpreter, that I may one day get working on my 8-bit AVR microcontroller.
haproxy-auth-request - auth-request allows you to add access control to your HTTP services based on a subrequest to a configured HAProxy backend.
julia - The Julia Programming Language
plugins - OPNsense plugin collection
Carp - A statically typed lisp, without a GC, for real-time applications.
eastend-notebook-syntax - Atom syntax theme - East End Notebook
Fennel - Lua Lisp Language
blog - Source code of my personal blog
sectorlisp - Bootstrapping LISP in a Boot Sector
serpent - Lua serializer and pretty printer.
hissp - It's Python with a Lissp.